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What does Machine Learning and Energy Efficiency have in Common?

Apr 16, 2018 9:10:53 AM



A recent Clean Energy Economy Minnesota (CEEM) profile story features 75F Machine Learning Developer Madhushan Tennakoon, who goes by Madhu (pronounced ma • du), sharing his role improving energy efficiency and occupant comfort through development of 75F building intelligence and predictive controls software.

75F employees like to share their "Why" (see video) - their reason for working at 75F. What is Madhu’s "why?" You can say that energy efficiency has always been on his mind, ever since he was young boy back in Sri Lanka, where power outages were a common occurrence. 

The CEEM team came to 75F to develop an employee profile that represents the career opportunities in the green, clean energy market. It's part of their "Names Behind The Numbers" series, highlighting people working in Minnesota's clean energy economy - a sector employing more than 57,000 Minnesotans. We felt Madhu's role as machine learning developer helped demonstrate how new roles are emerging around technologies, like applied IoT. 

Mahu has a degree in physics and electrical engineering from the University of Minnesota. Deepinder Singh, CEO, noticed Madhu’s talents while judging the IoT Fuse Hackathon in 2017. Deepinder extended a job offer and Madhu thankfully accepted the position as the Machine Learning Developer.

When considering the field of machine learning, your first thought might not go to energy efficiency. However, Minnesota's energy efficiency sector employs a whopping 86% of the state's clean energy workforce. 75F is a building intelligence company, bringing applied IoT and Machine Learning to improve building performance by creating optimal occupant experiences and reducing operating expenses (OpEx), with energy as the most immediate area of savings.

Madhu’s job is to teach the system to comprehend how a building absorbs heat, how it loses heat, how it responds to different heating and cooling loads and so on. This helps to make our system predictive and proactive. The building will start to learn and act according to standards and customer settings without you having to do anything; so, you can "set it and forget it" if you'd like. Though you have a wealth of monitoring and control options at your fingertips through the Web and mobile app.

Who would have thought that a machine learning career meant helping decrease carbon footprint in commercial buildings?

While CEEM was in our office for Madhu, we thought it’d be a great idea to see the system in action. We took the crew to a 75F retail installation at Amazing Lash Studio in Eagan, a beauty salon specializing in eyelash extensions - one of the hottest and fastest growing franchises. 75F is helping Amazing Lash is control many aspects of the indoor environment in the building. Madhu walked through the facility with CEEM and explained how the 75F system works, sharing firsthand what he is teaching the system to learn - from controlling the solar gain created by ample sunshine in the lobby, to controlling temperatures and humidity in the individual guest studios for both lash glue performance and customer comfort. This helps bring Madhu's algorithm work from the cloud down to real world benefits in comfort and efficiency. 

You can read Madhu's and other stories CEEM "Name Behind the Numbers" stories right here

Kelly Huang

Written by Kelly Huang

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